Predicting vancomycin trough serum concentration in augmented renal clearance patients through an artificial neural network model

Wang, Puxiu; Li, Bin; Luo, Yifan; Wang, Yidan; Jiang, Chunying; Chu, Yang

doi:10.1016/j.ipha.2023.08.004

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2024

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“…(3) Comprehensive: Traditional assessment methods take into account various physical indicators and physiological parameters, allowing for a comprehensive evaluation of the physical health of preschool children. This approach facilitates a holistic understanding of their health status [9] .…”

Section: Advantagesmentioning

confidence: 99%

Research on an intelligent assessment method for the physical health of preschool children based on the Artificial Neural Network (ANN) model

Li,

Malek,

Awang

2024

Environ. Soc. Psychol.

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This study aims to use the BP neural network model to predict the monthly total number of reported symptoms in preschool children, thereby achieving early warning for the total number of cases in the current month. By analyzing the training results of the neural network and the fitting of the model, the feasibility and effectiveness of the BP neural network in monitoring the physical health of preschool children are validated. The predictive model is of great significance for the prevention of infectious diseases in a border region of a certain province, providing important information for the local incidence situation. The research results indicate that the established BP neural network model demonstrates good accuracy and practicality in predicting the monthly total number of reported symptoms in preschool children’s physical health.

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Section: Advantagesmentioning

confidence: 99%